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Upcoming large scale telescope projects such as the Square Kilometre Array(SKA) will see high data rates and large data volumes; requiring tools that cananalyse telescope event data quickly and accurately. In modern radiotelescopes, analysis software forms a core part of the data read out, andlong-term software stability and maintainability are essential. AstroAccelerateis a many core accelerated software package that uses NVIDIA(R) GPUs to performrealtime analysis of radio telescope data, and it has been shown to besubstantially faster than realtime at processing simulated SKA-like data.AstroAccelerate contains optimised GPU implementations of signal processingtools used in radio astronomy including dedispersion, Fourier domainacceleration search, single pulse detection, and others. This article describesthe transformation of AstroAccelerate from a C-like prototype code to aproduction-ready software library with a C++ API and a Python interface; whilepreserving compatibility with legacy software that is implemented in C. Thedesign of the software library interfaces, refactoring aspects, and codingtechniques are discussed.

Development of production-ready GPU data processing pipeline software for AstroAccelerate